IMM_SMOOTH Fixed-interval IMM smoother using two IMM-filters. Syntax: [X_S,P_S,X_IS,P_IS,MU_S] = IMM_SMOOTH(MM,PP,MM_i,PP_i,MU,p_ij,mu_0j,ind,dims,A,Q,R,H,Y) In: MM - NxK matrix containing the means of forward-time IMM-filter on each time step PP - NxNxK matrix containing the covariances of forward-time IMM-filter on each time step MM_i - Model-conditional means of forward-time IMM-filter on each time step as a cell array PP_i - Model-conditional covariances of forward-time IMM-filter on each time step as a cell array MU - Model probabilities of forward-time IMM-filter on each time step p_ij - Model transition probability matrix mu_0j - Prior model probabilities ind - Indices of state components for each model as a cell array dims - Total number of different state components in the combined system A - State transition matrices for each model as a cell array. Q - Process noise matrices for each model as a cell array. R - Measurement noise matrices for each model as a cell array. H - Measurement matrices for each model as a cell array Y - Measurement sequence Out: X_S - Smoothed state means for each time step P_S - Smoothed state covariances for each time step X_IS - Model-conditioned smoothed state means for each time step P_IS - Model-conditioned smoothed state covariances for each time step MU_S - Smoothed model probabilities for each time step Description: Two filter fixed-interval IMM smoother. See also: IMM_UPDATE, IMM_PREDICTION, IMM_FILTER

- gauss_pdf GAUSS_PDF Multivariate Gaussian PDF
- kf_predict KF_PREDICT Perform Kalman Filter prediction step
- kf_update KF_UPDATE Kalman Filter update step

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